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WO2012112119A1 - Procédé et appareil pour l'analyse d'un échantillon liquide par spectroscopie raman - Google Patents

Procédé et appareil pour l'analyse d'un échantillon liquide par spectroscopie raman Download PDF

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Publication number
WO2012112119A1
WO2012112119A1 PCT/SG2011/000065 SG2011000065W WO2012112119A1 WO 2012112119 A1 WO2012112119 A1 WO 2012112119A1 SG 2011000065 W SG2011000065 W SG 2011000065W WO 2012112119 A1 WO2012112119 A1 WO 2012112119A1
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spectra
sers
raman
liquid sample
sers surface
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WO2012112119A8 (fr
Inventor
Md. Khalid NIZAMUDIN
Shaik SALIM
Effendi Widjaja
Geok Hong LIM
Marc Garland
Ajay Agarwal
Cheng Fang
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Agency for Science Technology and Research Singapore
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Agency for Science Technology and Research Singapore
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Priority to SG2013061445A priority patent/SG192753A1/en
Publication of WO2012112119A1 publication Critical patent/WO2012112119A1/fr
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/65—Raman scattering
    • G01N21/658—Raman scattering enhancement Raman, e.g. surface plasmons

Definitions

  • the present invention relates to analyzing a liquid sample by Raman spectroscopy. It particularly relates to techniques in which the liquid sample comprises multiple analyte components in a liquid medium.
  • Raman spectroscopy is a spectroscopic technique widely used as an analytical tool in the chemical sciences. It relies on the "Raman effect”, inelastic scattering of
  • monochromatic light usually from a laser in the visible, near infrared, or near ultraviolet range.
  • the laser light interacts with molecular vibrations, phonons or other excitations in the system, resulting in the energy of the laser photons being shifted up or down.
  • the shift in energy gives information about the phonon modes in the system.
  • Raman effect is small (it shifts the energy of only about 1 in every 10 9 photons in the incident laser light), so Raman spectroscopy is most easily performed with pure or concentrated substances. Raman spectroscopy is frequently used to identify the primary chemical constituents present in a macroscopic sample, and/or for quality control.
  • SERS Surface Enhanced Raman Spectroscopy
  • a complex molecule with many functional groups will have a very large number of vibrational bands, so that the Raman spectrum of even a single analyte can be very complicated. If a liquid sample contains multiple analytes the spectra will typically be overlapping, giving the sample as a whole a complex Raman spectrum. In most experimental situations the analytes are not known in advance, and they are not available in a pure form. For this reason, it may be essentially impossible to determine which analytes have contributed to the Raman spectrum of the liquid sample, so the SERS analysis fails.
  • BTEM is a blind-source-separation algorithm, which does not need to have any a priori information. Instead, BTEM needs a number of distinctly different spectra as input, each containing the pure component spectra in different proportions. The BTEM extracts the pure component spectra. It is thus a "self-modeling" curve resolution technique.
  • the BTEM technique has been successfully used to analyze data from FTIR (Fourier transform infrared spectroscopy), UV-VIS (Ultraviolet- Visible spectroscopy), NMR (nuclear magnetic resonance) spectroscopy and MS (mass-spectroscopy).
  • the present invention aims to provide methods and apparatus for analyzing a liquid sample containing multiple unknown analyte components.
  • the invention proposes that the liquid sample containing multiple analytes is used to produce a layer on a SERS surface (which may be a surface of a single SERS substrate, or the collective surfaces of multiple SERS substrates, or a surface of any other SERS device, such as SERS nanowires) and that multiple respective Raman spectra are collected from each of multiple locations on the SERS surface.
  • a SERS surface which may be a surface of a single SERS substrate, or the collective surfaces of multiple SERS substrates, or a surface of any other SERS device, such as SERS nanowires
  • multiple respective Raman spectra are collected from each of multiple locations on the SERS surface.
  • Each of the Raman spectra comprises multiple signal components which are pure component spectra from the corresponding multiple analytes.
  • the different Raman spectra have different respective ratios of those signal components.
  • the multiple Raman spectra are used to obtain information about the analytes.
  • a first possible reason that the Raman spectra contain different respective ratios of signal components from the multiple analytes is that the analytes are present in different proportions in the different locations. That is, the layer may be inhomogeneous.
  • the SERS surface is different in the different locations, leading at each location to the analytes generating Raman scattering in a different ratio. That is, the analytes may interact with the SERS surface in different ways at the different locations. For example, in the case of two analytes, a first of the analytes may generate more Raman scattering than the second analyte at a first location, and less Raman scattering than the second analyte at a second location, even though the concentrations of the first and second analytes are the same at both locations.
  • a self-modeling curve resolution technique such as BTEM may be applied to the multiple Raman spectra to extract the multiple pure component spectra.
  • the pure component spectra may be used to identify the analytes, such as by comparison with a reference library of one or more pre-known pure component spectra (which may have been originally obtained by experiment, or be a SERS spectrum, predicted from first principles, of a species believed to be present as an analyte).
  • pre-known pure component spectra which may have been originally obtained by experiment, or be a SERS spectrum, predicted from first principles, of a species believed to be present as an analyte.
  • there are possible applications of the invention without using pre-known spectra An example might be in a situation in which it is desired to make sure that there are no chlorinated organics in a water supply.
  • the water supply contains an analyte having a pure component spectrum with a strong band at circa 550- 800 cm “1 (indicative of C-Cl vibrations) and other at circa 800-1000 cm “1 (indicative of C-C vibrations) and distortions at circa 1200-1500 cm “1 (indicative of various C-H vibrational modes), then this suggests that an organic chloride is present, and there is no need for a reference library.
  • the liquid sample can be evaporated onto the SERS surface, and then respective Raman spectra are obtained from areas which are of microscopic size. These areas can be non-overlapping or partially overlapping.
  • the present inventors have discovered that typically on a microscopic scale the deposited analytes are heterogeneously distributed and/or the ration of signal contributions are heterogeneously distributed.
  • the regions have a maximum diameter in the range about 1 micro to about 20 microns, though slightly smaller and larger sizes are possible. The maximum diameter might for example be no more than 5 microns, or no more than 2 microns.
  • a Raman microscope, with spatial resolution of about 1 micron, can provide hundreds or thousands of distinct spectra from one sample.
  • the SERS substrate(s) may be formed with a surface which is inhomogeneous.
  • This inhomogeneous surface may improve the inhomogeneity of the deposited analyte layer which is produced during the evaporation process and/or create inhomogeneous levels of Raman scattering.
  • the inhomogeneity may be spatial (e.g. surface roughness or structure) and/or chemical (i.e. atomic composition).
  • the inventors have discovered that analytes in a liquid sample are adsorbed onto the inhomogeneous surface in different proportions on such a surface and/or the ratio of signals contributions are inhomogeneously distributed.
  • the use of an inhomogeneous surface thus makes it possible to obtain the layer on the SERS surface containing the spatially different proportions of analytes, even without evaporating the liquid of the sample away.
  • the Raman spectra can be collected by Raman spectroscopy of the adsorbed layer.
  • One possibility is for a SERS substrate to be employed which has different areas having spatially-differing surface.
  • a technique for fabricating such a SERS substrate with a inhomogeneous (but regular) three-dimensional surface is disclosed in R.Z. Tan et al "3D arrays of SERS substrate for ultrasensitive molecular detection", Sens. Actuators A: Phys. (2007); and A.
  • Another way to produce inhomogeneity in the surface of the SERS device is to form different areas of a single SERS substrate with different respective compositions, or alternatively to use multiple SERS devices having different compositions to collectively form the SERS surface.
  • the different compositions will in general have different adsorption characteristics, so that the analytes will be adsorbed to different relative levels in the different areas.
  • the spatially non-uniform adsorption of molecules means a greater variation in the measured Raman spectra from point-to-point on the SERS surface, and this variation is a crucial pre-requisite for successful BTEM analysis.
  • one way to produce inhomogenous composition is to form the SERS surface from an alloy of a first metal (such as gold or silver) having a strong SERS effect with at least one further material (e.g. another metal).
  • the further material may be an other element such as any alkali metal, transition metal, rare earth metal, metalloid or non-metallic element.
  • the further material is typically present in a much lower proportion than the first metal, such as under 10%, more preferably under 7%, and optionally at no more than 5% atomic concentration. In this case, variations in the concentrations of the further material— which arise spontaneously on the microscopic scale - lead to spatial variation of the analyte concentrations on the microscopic scale.
  • the SERS surface may comprise at least one area with a number of components of the alloy greater than two. Specifically if the first metal is alloyed with a number N of further materials which is at least 2 (referred to here an "N- component" alloy, where it is understood that N is at least 2), then the variations are greater. N-component alloys have many different domains on an atomic scale.
  • a 3 -component gold alloy (perhaps prepared from three binary alloys containing gold and respectively materials A, B, C in a proportion of say 1%) should have primarily domains of gold, but there will also be domains with isolated A, pairs of A, clusters of A, pairs of A-B, clusters of A-B, pairs A-C, clusters of A-B-C and so forth.
  • N-component alloys one can cover a lot of combinations rapidly and hence cover a lot of variations in preferential adsorption of the analyte mixture components.
  • N-component gold alloy SERS devices would cover compositions and hence preferential adsorptions that are not well represented by binary gold alloys (or even an "ensemble" of binary alloys, as described in the following paragraph). Signal variation should be enhanced for a set of
  • the SERS surface may be designed to include a first predetermined area which is a first metal in a pure state (e.g. substantially pure gold or silver) and a second area which is the first metal alloyed with at least one further material (that is, a binary alloy or an N-component alloy).
  • a third area which is the first metal alloyed with at least one other material. More generally, there be any number of areas (greater than two), each with a different respective chemical compositions.
  • a system in which there are multiple areas of the SERS surface with different compositions is called here an "ensemble". The areas typically have a size of at least 1 micron.
  • the multiple areas do not have to be distinct parts of a single integral (that is one-piece) SERS substrate. Instead, multiple, separate SERS substrate elements, having a different respective surface compositions, may be arranged (though not necessarily fixed together, or even touching each other) to form collectively a single SERS surface. If so, the adsorbed "layer" is composed of multiple layer portions: one on each of the devices. In principle, in some embodiments the layer portions need not be formed on all of the
  • a portion of a liquid sample may be used to form a first layer portion on a first SERS device, a second portion of the liquid sample may be used to form a second layer portion on a second SERS device, etc.
  • Locations in each of the two or more layer portions are then measured to generate respective Raman spectra, which are then combined to form a single dataset which is input to the BTEM algorithm.
  • the second layer portion may be formed after the first layer portion has been destroyed.
  • the variations in the composition of the surface produced by the use of the ensembles and/or the use of a binary alloy or N-component alloy surface have another effect, besides leading to an inhomogeneity in the distribution of the adsorbed analytes.
  • the varying composition may induce electronic changes in the SERS process itself. This, in turn, would lead to an inhomogenous Raman enhancement caused by the SERS effect even if the distribution of the analytes on the SERS surface were uniform. It is expected that the pure component spectra would be substantially the same at each location, but that their ratios in the total Raman spectrum for each location would differ.
  • the analyte components of a liquid sample may be measured only once by the present method. Alternatively, its analyte components may be measured repeatedly. This is particularly interesting in the case of a reacting liquid, since the progress of the reaction may be tracked.
  • the liquid sample may be static during the measurement.
  • liquid samples may be drawn from a fluid in a reservoir, and onto the SERS substrate as a continuous process. This permits a process of continuous monitoring, referred to here as a "flow-through" mode.
  • the fluid in the reservoir may be undergoing a chemical reaction, for example, and the method can be used to monitor this reaction.
  • the fluid in the reservoir may be not be undergoing a reaction, but may be subject to a risk of impurities being formed.
  • the invention may be useful for quality control (e.g. if the fluid is water). For example, there may be a process of determining whether the identified analytes comprise one of a number of proscribed materials (e.g. poisonous impurities), and in this case performing an alarm protocol.
  • Fig. 1 is a flow diagram of an embodiment of the invention
  • Fig. 2 is composed of Figs. 2(a) and (b), which are Raman spectra respectively of ibuprofen and caffeine deposited from a water sample onto a surface of an SERS substrate;
  • Fig. 3 is a visible light image of the surface of a SERS substrate onto which a liquid sample containing ibuprofen and caffeine has been evaporated in a first
  • Fig. 4 shows respective Raman spectra for 121 pixels on the SERS substrate of
  • Fig. 5 is composed of Figs. 5(a)-5(d), and shows pure component spectra obtained from me spectra of Fig. 4, and me spatial distribution of the components;
  • Fig. 6 is a comparison of the spectrum of Fig. 5(a) with a reference spectrum
  • Fig. 7 is a comparison of the spectrum of Fig. 5(b) with a reference spectrum
  • Fig. 8 is composed of Figs. 8(a)-8(f) and shows visual images and Raman spectra for three areas of a SERS substrate in a second experiment
  • Fig. 9 shows pure component spectra obtained from the spectra of Fig. 8.
  • Fig. 10 is composed of Figs. 10(a) and 10(b), and compares of the spectra of Fig. 9 with reference spectra;
  • Fig. 11 indicates the spatial distribution of the components shown in Fig. 9 in one of the areas of the SERS substrate of Fig. 8;
  • Fig. 12 shows schematically an apparatus which is an embodiment of the invention
  • Fig. 13 is composed of Figs. 13(a)-13(f) and shows visual images and Raman spectra for three areas of a SERS substrate in a third experiment, performed using the apparatus of Fig. 12;
  • Fig. 14 shows two spectra obtained from the Raman spectra of Fig. 13;
  • Fig. 15 is composed of Figs. 15(a) and 15(b) and is comparisons of the spectra of Fig. 14 with reference spectra;
  • Fig. 16 is composed of Figs. 16(a) to 16(c), and indicates the spatial distribution of the components shown in Fig. 14 in one of the areas of the SERS substrate of Fig. 13; .
  • Fig. 17 shows Raman spectra from three areas of a SERS substrate in a fourth experiment
  • Fig. 18 shows six spectra obtained from the Raman spectra of Fig. 17;
  • Fig. 19 is comparisons of the spectra of Fig. 18 with reference spectra;
  • Fig. 20 is composed of Figs. 20(a) and (b), and compares pure component spectra for two analytes obtained using various different SERS surfaces, and by combining the data from these surfaces;
  • Fig. 21 shows Raman spectra from three areas of a SERS substrate in a fifth experiment
  • Fig. 22 shows two spectra obtained from the Raman spectra of Fig. 21;
  • Fig. 23 is comparisons of the spectra of Fig. 22 with reference spectra; and Fig. 24 is composed of Figs. 24(a) and 24(b), and compares pure component spectra for two analytes obtained using various different SERS surfaces, and by combining the data from these surfaces.
  • Fig. 1 shows the overall flow diagram of a method which is an embodiment of the invention.
  • a first step a mixture of analytes is combined with a fluid to form a liquid sample.
  • a second step the liquid sample is used to form a layer on the surface of an SERS surface in which the analytes are present in differing proportions at each of a number of "pixels”.
  • step 3 Raman spectra are collected in respect of each of the pixels.
  • a fourth step (step 4), the BTEM method is used to obtain pure component spectra in respect of each of the analytes.
  • a fifth step (step 5) is performed, in which the pure component spectra are identified using a library of pure component spectra, or by comparison with a first-principles predicted SERS spectrum of a species believed to be present as an analyte.
  • Fig. 2(a) shows the pure component reference spectrum obtained for ibuprofen
  • Fig. 2(b) shows the corresponding pure component reference spectrum obtained for caffeine.
  • a sample of water containing a mixture of caffeine and ibuprofen was deposited on the SERS substrate.
  • a Raman microscope was then used to collect a Raman spectrum from each of a 121 pixels on the substrate (specifically, the area of the substrate used was 200x200 microns, with a step size between pixel measurements of 20 microns) to give corresponding mixture SERS spectra.
  • Fig 3 shows a visible light microscopy image of the SERS substrate after evaporation of the solution. It is clear that some sort of pattern now exists on the surface.
  • Fig 4 shows the corresponding Raman spectra from the 121 pixels. Clearly, the spectra in each pixel are quite different, implying the heterogeneous nature of the deposited layer.
  • a BTEM analysis was performed on the 121 spectra. Two patterns were recovered, as shown in Fig. 5(a) and 5(b).
  • Figs. 5(c) and 5(d) are corresponding plots showing spatial distributions of the corresponding intensities of the respective patterns across the SERS surface, where the intensity is marked by a corresponding level of shading. The right side of Figs. 5(c) and 5(d) shows the key to the levels of shading.
  • Raman point-by-point mapping was performed on three areas of the SERS substrate which had been exposed to the mixture sample.
  • the mapping size for each area was 80 ⁇ by 80 ⁇ .
  • the interval step size for each mapping was 10 ⁇ .
  • 81 Raman mixture spectra were collected, and de-spiked and baseline corrected.
  • Figs. 8(a) to 8(c) are visible microscopy images of the three areas.
  • Figs. 8(d) to 8(f) show the corresponding Raman mixture spectra after de-spiking and baseline correction.
  • Fig. 9 is attributable to a background signal due to the SERS device.
  • the third and fourth lines in Fig. 9 were additional and unexpected pure component spectral estimates. These may involve impurities from the solution preparations, the contact with the air, or even some sort of degradation compounds arising from exposure of the methylene blue / rhodamine B to air while adsorbed on the surface.
  • Figure 11 illustrates how the embodiment can be used to find the spatial distribution for the components in the portion of the SERS substrate contacted by the mixture sample.
  • the left part of Fig. 11 is the central visual image from the upper row of Fig. 8. The left of the image is the interior of the droplet and last part of the spot to dry.
  • the central part of Fig. 11 is the same as Fig. 9.
  • the right part of Fig. 11 shows, for each pixel of the visual image, the corresponding signal intensity of each of the five components. These were obtained by mapping the pure component spectral estimates back onto the experimental measurements and obtaining the weighting for each component. Note the non-uniform concentrations of the components in the analysis area
  • concentration of the dopant material alloys with very high weight percentage of the dopant will probably not exhibit good performance. Therefore, dilute alloys are preferable. Concentrations of about 5% and below are believed to be preferable.
  • the water 122 was drawn from the reservoir 121 through a conduit 123 by a peristaltic pump 124, and into a Teflon holder 125 containing the SERS chip, before returning to the reservoir 121, so that the flow was cyclic.
  • a Raman microscope 126 was focused on the SERS chip which was mounted in the Teflon holder 125. CaF2 and ZnSe single crystals were used at various times as windows for the holder 125.
  • Each mapping area size was 400 ⁇ by 400 ⁇ .
  • the interval step size for each mapping was 50 ⁇ .
  • 81 Raman mixture spectra were collected.
  • Figs. 13(a), (b) and (c) show the visible microscopy of the mapping areas
  • Figs. 13(d), (e) and (f) show the corresponding Raman mapping data, following de-spiking and baseline correction.
  • the visible microscopy shows, the surfaces appear spatially homogeneous.
  • the associated sets of Raman spectra show that in fact, there is pixel-to-pixel variation for the signals.
  • the collected mixture spectra from three areas, after de-spiking and baseline-correction, were collected together for BTEM analysis.
  • Figure 14 shows the BTEM spectral estimates of the underlying individual component spectra. In contrast to the
  • Fig. 15 shows how the two pure component spectra of Fig. 14 are identified, by comparison of them with reference spectra obtained from methylene blue and rhodamine B.
  • the two lines of Fig. 14 are marked as lines 21 and 22, and the reference spectra as lines 23 and 24. It can be seen that BTEM analysis has successfully deconvoluted the mixture spectra into the underlying pure component spectra.
  • Fig. 16 shows a typical spatial distribution for the components in the mixture analysis.
  • Fig. 16(a) is the visible microscopy image Fig. 13(c).
  • Fig. 16(b) the pure component
  • BTEM spectral estimates of Fig. 14, and Fig. 16(c) is the resulting spatial distributions, with the right hand part of the figure being scales indicating the meaning of the shading levels.
  • Fig. 16(c) was obtained by mapping the pure component spectral estimates back onto the experimental measurements and getting the weighting for each component. Note the non-uniform concentrations of the components in the analysis area.
  • SERS analysis there are several possible applications for flow-through SERS analysis combined with BTEM analysis.
  • one application would be the use of a SERS chip and BTEM for an HPLC (high-performance liquid chromatograph).
  • HPLC high-performance liquid chromatograph
  • the 4 th experiment resembled the 1 st and 2 nd experiments, except that instead of a single SERS substrate, the experiment employed multiple SERS substrates, each having a SERS surface with a different respective alloy composition. We refer to such a combination of different surfaces as an "ensemble".
  • Raman spectra obtained from the set of SERS substrates were combined to give a single dataset which was then input to the BTEM algorithm.
  • the compositions were selected from the following possibilities, corresponding respectively to the eight substrates used in the 2 nd experiment: Au, 1 % Rh/Au, 1% Ce/Au, 1% Mn/Au, 0.15% P/Au, 1% Ca/Au, 2.5% Ca/Au, 5% Ca/Au.
  • test mixtures consisted of methylene blue and rhodamine B in water.
  • the use of multiple SERS substrates is equivalent to forming the ensemble as a single SERS device having many sectors with different respective alloy compositions.
  • Such a device can be formed by simply mounting a mosaic of the individual SERS devices (each having a SERS surface of a single respective composition) on the same holder.
  • a SERS device could be formed by using a mask to cover a silicon substrate and then depositing a first alloy (e.g. Rh/Au), then removing the mask and depositing a different mask, and depositing a second alloy (e.g. Ca/Au) etc.
  • a first alloy e.g. Rh/Au
  • second alloy e.g. Ca/Au
  • Figure 19 shows a comparison of methylene blue and rhodamine B pure component spectra 31, 32 obtained from BTEM estimates from the ensemble of 3 gold-alloys, and reference spectra 33, 34.
  • the BTEM estimates of methylene blue and rhodamine B have a high degree of similarity to the pure references.
  • Figure 20(a) shows the methylene blue spectra obtained by a BTEM analysis of the l%Rh/Au area only (bottom line), the l%Mn/Au area only (middle line), and the ensemble of 3 gold-alloys (top line).
  • Figure 20(b) shows the Rhodamine B spectra obtained by a BTEM analysis of the 1% Ca/Au area only (bottom line), the l%Rh/Au area only (2 nd line from the bottom), the l%Mn/Au area only (3 rd line from the bottom), and the ensemble of 3 gold-alloys (top line).
  • the analysis of the ensemble of 3 gold-alloys provided, in general, better signal-to-noise ratios for the spectral estimates (particularly for Rhodamine B, for which the top line in Fig. 20(b) is considerably less noisy than the other three).
  • the advantages of an ensemble of gold and gold-alloys for mixture analysis is anticipated to become more marked as one goes from 2-solute systems to 3-solute systems and to more complex systems.
  • the 5 th experiment used the flow-through arrangement of the 3 rd embodiment, but with the ensembles of the 4 th experiment.
  • RAMAN spectra are collected at multiple respective locations within each of the areas.
  • the total set of SERS spectra are shown in Fig. 21. Note that there is a lot of variation in the signals.
  • Fig. 22 shows the BTEM spectral estimates of the underlying pure component spectra. In these flow-through experiments, no extra unknown spectra were discovered. This contrasts with the assay analysis of the 4 th experiment.
  • Fig. 23 shows the comparison of the methylene blue and rhodamine B pure component spectra 41, 42 (shown in Fig. 22) obtained by BTEM from the ensemble of 3 gold- alloys, with reference specta 43, 44.
  • the lines 41 and 42 have a high degree of similarity to the lines 43, 44. In fact, lines 41 and 43 are so close as to be almost indistinguishable.
  • Fig. 24 shows a comparison of BTEM analyses of l%Mn/Au & l%Rh/Au & 0.15% P/Au individually and the BTEM analysis from the ensemble of gold-alloys.
  • the BTEM analysis of the ensemble of gold-alloys provided much better signal-to-noise ratios for both of the spectral estimates.
  • the Rhodamine B is much better resolved, as demonstrated by the portions of the spectra for l%Mn/Au and l%Rh/Au shown dashed.
  • the advantages of an ensemble of gold and gold-alloys for mixture analysis is anticipated to become more marked as one goes from 2-solute systems to 3 -solute systems and to more complex systems.
  • the 2 nd to 5 th experiments were performed with binary gold alloys (i.e. gold plus one other component which is an alloy material), but they can also be performed with N-component gold alloys (with N being an integer greater than 2).

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Abstract

Selon la présente invention, un échantillon liquide contenant des analytes multiples est utilisé pour produire une couche sur une surface SERS d'un substrat SERS. Des spectres Raman sont recueillis à partir des différents emplacements. Les spectres Raman pour des emplacements différents ont des rapports différents des composantes de signal des analytes respectifs multiples, par exemple car les analytes sont présents dans des proportions différentes aux différents emplacements, ou car les analytes interagissent avec la surface SERS de manières différentes aux différents emplacements. Une technique de résolution de courbe auto-modelante telle que BTEM est utilisée pour extraire à partir des spectres Raman recueillis de multiples spectres de composants purs, correspondant aux composants d'analytes respectifs. Les spectres de composants purs peuvent être utilisés pour identifier les analytes. Une façon de produire la couche inhomogène est d'évaporer l'échantillon liquide. Une autre est de disposer la surface du substrat SERS de sorte qu'elle soit inhomogène, de sorte qu'une couche inhomogène d'analytes adsorbés soit formée et/ou de telle sorte que l'effet SERS lui-même soit inhomogène.
PCT/SG2011/000065 2011-02-16 2011-02-16 Procédé et appareil pour l'analyse d'un échantillon liquide par spectroscopie raman Ceased WO2012112119A1 (fr)

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SG2013061445A SG192753A1 (en) 2011-02-16 2011-02-16 Method and apparatus for analyzing a liquid sample by raman spectroscopy

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Cited By (4)

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Publication number Priority date Publication date Assignee Title
CN103940934A (zh) * 2014-03-25 2014-07-23 张华俊 一种分析混合物成分的方法
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CN103940934A (zh) * 2014-03-25 2014-07-23 张华俊 一种分析混合物成分的方法
WO2016041842A1 (fr) 2014-09-17 2016-03-24 Danmarks Tekniske Universitet Procédé et système de détection d'un analyte cible
CN104267108A (zh) * 2014-09-23 2015-01-07 广西壮族自治区药用植物园 一种基于mrem化学计量法与色谱联用的中药成分分析方法
WO2023205279A1 (fr) * 2022-04-19 2023-10-26 The Johns Hopkins University Spectroscopie raman améliorée avec addition de composés aromatiques

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